A Extended Set-membership Identification for Time-varying Systems with Random Parametric Perturbation

摘要

This paper proposes the Genetic Algorithm (GA) based new parameter bound estimation method for time-varying system with random parametric perturbations. This method is extending and improving the Setmembership Identification (SI) method from the point of view that linear time-varying systems are identified. Proposed method is able to get the more precise parameter bounds than the result by usual SI method. Furthermore, some numerical results for the low ordered plant models are also included to show the applicability and the effectiveness of the proposed method.